Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Deng, Min"'
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing, 2023
Semantic segmentation is a key technique involved in automatic interpretation of high-resolution remote sensing (HRS) imagery and has drawn much attention in the remote sensing community. Deep convolutional neural networks (DCNNs) have been successfu
Externí odkaz:
http://arxiv.org/abs/2208.07722
A critical challenge problem of scene change detection is that noisy changes generated by varying illumination, shadows and camera viewpoint make variances of a scene difficult to define and measure since the noisy changes and semantic ones are entan
Externí odkaz:
http://arxiv.org/abs/1810.09111
Human vision possesses strong invariance in image recognition. The cognitive capability of deep convolutional neural network (DCNN) is close to the human visual level because of hierarchical coding directly from raw image. Owing to its superiority in
Externí odkaz:
http://arxiv.org/abs/1708.01420
Autor:
Li, Haifeng, Dou, Xin, Tao, Chao, Hou, Zhixiang, Chen, Jie, Peng, Jian, Deng, Min, Zhao, Ling
In recent years, deep convolutional neural network (DCNN) has seen a breakthrough progress in natural image recognition because of three points: universal approximation ability via DCNN, large-scale database (such as ImageNet), and supercomputing abi
Externí odkaz:
http://arxiv.org/abs/1705.10450
Recently, deep convolutional neural network (DCNN) achieved increasingly remarkable success and rapidly developed in the field of natural image recognition. Compared with the natural image, the scale of remote sensing image is larger and the scene an
Externí odkaz:
http://arxiv.org/abs/1705.07077